Add support for reading company ticker data from local

README.md

@@ -400,11 +400,12 @@ The data is stored by default in the `~/.edgar` directory. You can change this b
 ```bash
 
 ```python
-def download_edgar_data(submissions: bool = True, facts: bool = True):
+def download_edgar_data(submissions: bool = True, facts: bool = True, reference: bool = True):
     """
     Download all the company data from Edgar
     :param submissions: Download all the company submissions
     :param facts: Download all the company facts
+    :param reference: Download reference data
     """
 download_edgar_data()
 

edgar/core.py

@@ -252,6 +252,9 @@ def download_edgar_data(submissions: bool = True,
     if facts:
         from edgar.entities import download_facts
         download_facts()
+    if reference:
+        from edgar.reference import download_reference_data
+        download_reference_data()
 
 
 class InvalidDateException(Exception):

edgar/reference/tickers.py

@@ -1,16 +1,18 @@
 import re
+import os
+import json
 from functools import lru_cache
 from io import StringIO
 from pathlib import Path
-from typing import Optional, Union, List
+from typing import Optional, Union, List, Dict, Any
 
 import pandas as pd
 import pyarrow as pa
 from httpx import HTTPStatusError
 
 from edgar.httprequests import download_file, download_json, download_datafile
 from edgar.reference.data.common import read_parquet_from_package
-from edgar.core import log
+from edgar.core import log, get_edgar_data_directory
 
 __all__ = ['cusip_ticker_mapping', 'get_ticker_from_cusip', 'get_company_tickers', 'get_icon_from_ticker', 'find_cik',
            'get_cik_tickers', 'get_company_ticker_name_exchange', 'get_companies_by_exchange',
@@ -37,6 +39,20 @@ def cusip_ticker_mapping(allow_duplicate_cusips: bool = True) -> pd.DataFrame:
         df = df[~df.index.duplicated(keep='first')]
     return df
 
+
+def load_tickers_from_local() -> Optional[Dict[str, Any]]:
+    """
+    Load tickers from local data
+    """
+    reference_dir = get_edgar_data_directory() / "reference"
+    if not reference_dir.exists():
+        return None
+    company_tickers_file = reference_dir / os.path.basename(company_tickers_json_url)
+    if not company_tickers_file.exists():
+        return None
+    return json.loads(company_tickers_file.read_text())
+
+
 @lru_cache(maxsize=1)
 def get_company_tickers(
         as_dataframe: bool = True,
@@ -63,8 +79,13 @@ def get_company_tickers(
     ])
 
     try:
-        # Download JSON data
-        tickers_json = download_json(company_tickers_json_url)
+        if os.getenv("EDGAR_USE_LOCAL_DATA"):
+            tickers_json = load_tickers_from_local()
+            if not tickers_json:
+                tickers_json = download_json(company_tickers_json_url)
+        else:
+            # Download JSON data
+            tickers_json = download_json(company_tickers_json_url)
 
         # Pre-allocate lists for better memory efficiency
         ciks = []
@@ -110,18 +131,36 @@ def get_company_tickers(
         log.error(f"Error fetching company tickers from [{company_tickers_json_url}]: {str(e)}")
         raise
 
+def load_cik_tickers_from_local() -> Optional[str]:
+    """
+    Load tickers.txt from local data
+    """
+    reference_dir = get_edgar_data_directory() / "reference"
+    if not reference_dir.exists():
+        return None
+    tickers_txt_file = reference_dir / os.path.basename(ticker_txt_url)
+    if not tickers_txt_file.exists():
+        return None
+    return tickers_txt_file.read_text()
+
 def get_cik_tickers_from_ticker_txt():
     """Get CIK and ticker data from ticker.txt file"""
     try:
-        source = StringIO(download_file(ticker_txt_url, as_text=True))
+        if os.getenv("EDGAR_USE_LOCAL_DATA"):
+            ticker_txt = load_cik_tickers_from_local()
+            if not ticker_txt:
+                ticker_txt = download_file(ticker_txt_url, as_text=True)
+        else:
+            ticker_txt = download_file(ticker_txt_url, as_text=True)
+        source = StringIO(ticker_txt)
         data = pd.read_csv(source,
                            sep='\t',
                            header=None,
                            names=['ticker', 'cik']).dropna()
         data['ticker'] = data['ticker'].str.upper()
         return data
     except Exception as e:
-        log.error(f"Error fetching company tickers from [{company_tickers_json_url}]: {str(e)}")
+        log.error(f"Error fetching company tickers from [{ticker_txt_url}]: {str(e)}")
         return None
 
 @lru_cache(maxsize=1)